Senior AI Platform Engineer: DevOps & Observability

EY; Olympia (WA); Hybrid; USD 128,000 - 201,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Hybrid work model

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for its AI-native platform. You will shape how AI services are built, deployed, and governed across cloud, on‑prem, edge, and air-gapped environments, collaborating with senior engineers to test and evolve capabilities.

The role blends DevOps, MLOps, FinOps, and observability, demanding strong experience with GPU inference, CI/CD, and multi‑environment pipelines.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering, with hands-on ownership of AI workloads.
• Hands-on CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong experience with observability stacks and OpenTelemetry.
• Experience with cost management / FinOps tooling and quota enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.
• Proven track record delivering AI workloads under compliance constraints.
• Ability to define clean ownership boundaries with platform, trust, and data teams.

Responsibilities

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines, including automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets and model metadata, registries, and license management.
• Own resource and cost management with quotas and attribution to keep AI execution bounded.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI evaluation tooling.
• Own OpenTelemetry collection layer, including multi-tenant receivers and GPU telemetry exporters.
• Automate GitOps-based delivery and verification with policy gates built into pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure identity-stamped telemetry and per-tenant cost signals across workloads.

Skills

DevOps

Model-serving

Observability

FinOps

Governance

Cloud/on-prem

Communication

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

OpenTelemetry

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for its AI-native platform. You will shape how AI services are built, deployed, and governed across cloud, on‑prem, edge, and air-gapped environments, collaborating with senior engineers to test and evolve capabilities.

The role blends DevOps, MLOps, FinOps, and observability, demanding strong experience with GPU inference, CI/CD, and multi‑environment pipelines.